DISECTOR PROGRAM FOR UNBIASED ESTIMATION OF PARTICLE NUMBER, NUMERICAL DENSITY AND MEAN VOLUME

Zoltán Tomori, Ivan Krekule, Lucie Kubínová

Abstract

A DISECTOR program is presented, offering the possibility to count particles by the disector or unbiased sampling brick principles as well as to apply the point-counting method needed for estimation of the particle volume density or mean particle volume. Three modes of counting, two semi-automatic and one automatic, are offered, allowing the user to choose the one most suitable for his image data. In a semi-automatic regime, the user marks and counts individual particles by a mouse during browsing through the stack of images. In the algorithm working in an automated mode, the role of a human operator is suppressed, assuming that segmented objects are available in individual levels. The settings of the point grid and 3-D probe can be tailored for each application. The DISECTOR program applications are shown on the examples of the estimation of the number and numerical density of mesophyll cells in a Norway spruce needle and the mean volume of tubular cells in a chick embryonic kidney.